9.4.1.3 Variability of Temperature from Observations and Models

Year-to-year variability of global mean temperatures simulated by the most recent models compares reasonably well with that of observations, as can be seen by comparing observed and modelled variations in Figure 9.5a. A more quantitative evaluation of modelled variability can be carried out by comparing the power spectra of observed and modelled global mean temperatures. Figure 9.7 compares the power spectrum of observations with the power spectra of transient simulations of the instrumental period. This avoids the need to compare variability estimated from long control runs of models with observed variability, which is difficult because observations are likely to contain a response to external forcings that cannot be reliably removed by subtracting a simple linear trend. The simulations considered contain both anthropogenic and natural forcings, and include most 20th Century Climate in Coupled Models (20C3M) simulations in the MMD at PCMDI. Figure 9.7 shows that the models have variance at global scales that is consistent with the observed variance at the 5% significance level on the decadal to inter-decadal time scales important for detection and attribution. Figure 9.8 shows that this is also generally the case at continental scales, although model uncertainty is larger at smaller scales (Section 9.4.2.2).

Figure 9.7. Comparison of variability as a function of time scale of annual global mean temperatures (°C2 yr–1) from the observed record (Hadley Centre/Climatic Research Unit gridded surface temperature data set (HadCRUT3), Brohan et al., 2006) and from AOGCM simulations including both anthropogenic and natural forcings. All power spectra are estimated using a Tukey-Hanning filter of width 97 years. The model spectra displayed are the averages of the individual spectra estimated from individual ensemble members. The same 58 simulations and 14 models are used as in Figure 9.5a. All models simulate variability on decadal time scales and longer that is consistent with observations at the 10% significance level. Further details of the method of calculating the spectra are given in the Supplementary Material, Appendix 9.C.

Figure 9.8. As Figure 9.7, except for continental mean temperature. Spectra are calculated in the same manner as Figure 9.7. See the Supplementary Material, Appendix 9.C for a description of the regions and for details of the method used. Models simulate variability on decadal time scales and longer that is consistent with observations in all cases except two models over South America, five models over Asia and two models over Australia (at the 10% significance level).

Detection and attribution studies routinely assess if the residual variability unexplained by forcing is consistent with the estimate of internal variability (e.g., Allen and Tett, 1999; Tett et al., 1999; Stott et al., 2001; Zwiers and Zhang, 2003). Furthermore, there is no evidence that the variability in palaeoclimatic reconstructions that is not explained by forcing is stronger than that in models, and simulations of the last 1 kyr show similar variability to reconstructions (Section 9.3.3.2). Chapter 8 discusses the simulation of major modes of variability and the extent to which they are simulated by models (including on decadal to inter-decadal time scales).